Apache Maka vs OneCLI: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Apache Maka and OneCLI — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Apache Maka
The Apache Software Foundation
Apache-licensed local-first agent workspace that runs tools in a sandbox and records every model message and tool call as a recoverable execution log.
Key features
- Append-Only Execution Record: Model messages, tool calls, tool results, permission decisions, and turn termination events are written down durably, so the transcript is evidence rather than a disposable chat buffer.
- Context Trimming Without Data Loss: Old tool output can be omitted from the next prompt to shorten context while the full saved history remains intact and inspectable.
- Single Runtime Host: Desktop, terminal, and evaluation all execute through one runtime, so behavior does not diverge between how you develop and how you benchmark.
- Sandboxed Tool Boundary: Built-in Read, Write, Edit, Bash, Glob, and Grep tools run under a sandbox; anything leaving that boundary requires approval, and Computer Use and catalog skills are opt-in.
- Crash Recovery and Resume: Runs can be aborted, failures are classified, and an interrupted turn can optionally be resumed rather than restarted from scratch.
- Session Branching and Search: The desktop workspace supports creating, archiving, searching, renaming, retrying, regenerating, and branching sessions from any turn.
- Bring Your Own Model: Connect a cloud API, a locally hosted model, or a compatible gateway, with streaming output, thinking, usage reporting, and clearer provider errors.
- Declarative Evaluation Harness: maka eval expands multi-arm experiments into task by repetition by subject cells with immutable per-cell attempts and a result kernel covering score, normalized usage, attributable cost, duration, and failure reason.
- Local-First Storage: Sessions, settings, artifacts, and run records stay on the machine by default, with local memory and optional web search when configured.
Best for
- Auditable Agent Runs: Keeping a defensible record of exactly what an agent did and which permissions were granted during a task.
- Long Coding Sessions: Working through a multi-turn refactor with branching and resume instead of losing state when a turn fails.
- Agent Benchmarking: Running reproducible multi-arm experiments comparing models, prompts, or external agent subjects on the same task set.
- Air-Gapped or Regulated Work: Running an agent workspace where sessions and artifacts must remain on local infrastructure.
- Cost and Usage Analysis: Attributing token usage, cost, and duration per experiment cell to decide which model configuration to ship.
- Terminal Workflows: Driving an agent from the current project directory or scripting a single non-interactive turn from CI or a shell.
- Open-Source Agent Research: Building on a permissively licensed runtime whose execution semantics and architecture are fully documented.
OneCLI
OneCLI
An open-source platform giving every employee a sandboxed AI agent that reaches company tools through a credential gateway and never holds a real secret.
Key features
- Per-Request Credential Injection: The OneCLI gateway injects scoped credentials for each call so agents never hold a real secret, and keys never leave the vault.
- Isolated VM Per Employee: Every employee's agent runs in its own virtual machine, keeping one person's agent workload and data separated from everyone else's.
- Hard Policy Limits Outside the Model: Destructive actions such as deleting a repository, sending a payment or wiping a customer record are blocked by external enforcement rather than by asking the model to behave.
- Runaway Agent Circuit Breaker: An agent that starts repeating itself or acting far faster than a person would is automatically slowed or paused before it can cause damage.
- Human Approval Gates: Sensitive steps — like emailing a customer — pause with the work already prepared and wait for a team member's explicit go-ahead.
- Access Inheritance: An agent can only reach the tools and accounts its owner already has, so support cannot reach billing and nobody shares a password.
- Slack, CLI and SDK Interfaces: Employees can chat with their agent directly in Slack or drive it programmatically through the OneCLI CLI and SDK.
- Open Source with Self-Hosting: The platform is open source, and Enterprise customers can deploy it entirely inside their own infrastructure with SSO and SAML.
Best for
- Company-Wide Assistant Rollout: Give every employee an autonomous agent without handing out shared credentials or standing API keys.
- Regulated Workflow Automation: Automate finance or customer operations where certain actions must be provably impossible for an agent to take.
- Slack-Native Task Delegation: Ask an agent in Slack to complete a multi-step job across internal tools and get pinged only when a human decision is needed.
- Least-Privilege Agent Access: Scope each department's agent to that department's systems so support, engineering and billing stay in their own lanes.
- Security Review of Agent Activity: Use audit-log retention and resource-level scoping to reconstruct exactly what an agent touched and when.
- Self-Hosted Enterprise Deployment: Run the whole agent platform inside your own network with SSO, SAML and custom integrations.